double H1Seminorm(
const Mesh& mesh,
const CellFilter& filter,
const Expr& f,
const QuadratureFamily& quad,
const WatchFlag& watch)
{
Expr grad = gradient(mesh.spatialDim());
return L2Norm(mesh, filter, grad*f, quad, watch);
}
void Vector :: SetRandom ()
{
INDEX i;
for (i = 1; i <= Length(); i++)
Elem(i) = rand ();
double l2 = L2Norm();
if (l2 > 0)
(*this) /= l2;
// Elem(i) = 1.0 / double(i);
// Elem(i) = drand48();
}
double
PatchSideDataNormOpsComplex::RMSNorm(
const boost::shared_ptr<pdat::SideData<dcomplex> >& data,
const hier::Box& box,
const boost::shared_ptr<pdat::SideData<double> >& cvol) const
{
TBOX_ASSERT(data);
double retval = L2Norm(data, box, cvol);
if (!cvol) {
retval /= sqrt((double)numberOfEntries(data, box));
} else {
retval /= sqrt(sumControlVolumes(data, cvol, box));
}
return retval;
}
double
PatchSideDataNormOpsReal<TYPE>::RMSNorm(
const boost::shared_ptr<pdat::SideData<TYPE> >& data,
const hier::Box& box,
const boost::shared_ptr<pdat::SideData<double> >& cvol) const
{
// SGS
TBOX_ASSERT(data);
double retval = L2Norm(data, box, cvol);
if (!cvol) {
retval /= sqrt((double)numberOfEntries(data, box));
} else {
TBOX_ASSERT_OBJDIM_EQUALITY2(*data, *cvol);
retval /= sqrt(sumControlVolumes(data, cvol, box));
}
return retval;
}
int main(int argc, char** argv)
{
try
{
Sundance::init(&argc, &argv);
int np = MPIComm::world().getNProc();
int nx = 48;
int ny = 48;
int npx = -1;
int npy = -1;
PartitionedRectangleMesher::balanceXY(np, &npx, &npy);
TEUCHOS_TEST_FOR_EXCEPT(npx < 1);
TEUCHOS_TEST_FOR_EXCEPT(npy < 1);
TEUCHOS_TEST_FOR_EXCEPT(npx * npy != np);
MeshType meshType = new BasicSimplicialMeshType();
MeshSource mesher = new PartitionedRectangleMesher(0.0, 1.0, nx, npx,
0.0, 1.0, ny, npy, meshType);
Mesh mesh = mesher.getMesh();
CellFilter interior = new MaximalCellFilter();
CellFilter bdry = new BoundaryCellFilter();
/* Create a vector space factory, used to
* specify the low-level linear algebra representation */
VectorType<double> vecType = new EpetraVectorType();
/* create a discrete space on the mesh */
DiscreteSpace discreteSpace(mesh, new Lagrange(1), vecType);
/* initialize the design, state, and multiplier vectors */
Expr alpha0 = new DiscreteFunction(discreteSpace, 1.0, "alpha0");
Expr u0 = new DiscreteFunction(discreteSpace, 1.0, "u0");
Expr lambda0 = new DiscreteFunction(discreteSpace, 1.0, "lambda0");
/* create symbolic objects for test and unknown functions */
Expr u = new UnknownFunction(new Lagrange(1), "u");
Expr lambda = new UnknownFunction(new Lagrange(1), "lambda");
Expr alpha = new UnknownFunction(new Lagrange(1), "alpha");
/* create symbolic differential operators */
Expr dx = new Derivative(0);
Expr dy = new Derivative(1);
Expr grad = List(dx, dy);
/* create symbolic coordinate functions */
Expr x = new CoordExpr(0);
Expr y = new CoordExpr(1);
/* create target function */
const double pi = 4.0*atan(1.0);
Expr uStar = sin(pi*x)*sin(pi*y);
/* create quadrature rules of different orders */
QuadratureFamily q1 = new GaussianQuadrature(1);
QuadratureFamily q2 = new GaussianQuadrature(2);
QuadratureFamily q4 = new GaussianQuadrature(4);
/* Regularization weight */
double R = 0.001;
double U0 = 1.0/(1.0 + 4.0*pow(pi,4.0)*R);
double A0 = -2.0*pi*pi*U0;
/* Form objective function */
Expr reg = Integral(interior, 0.5 * R * alpha*alpha, q2);
Expr fit = Integral(interior, 0.5 * pow(u-uStar, 2.0), q4);
Expr constraintEqn = Integral(interior,
(grad*lambda)*(grad*u) + lambda*alpha, q2);
Expr L = reg + fit + constraintEqn;
Expr constraintBC = EssentialBC(bdry, lambda*u, q2);
Functional Lagrangian(mesh, L, constraintBC, vecType);
LinearSolver<double> solver
= LinearSolverBuilder::createSolver("amesos.xml");
RCP<ObjectiveBase> obj = rcp(new LinearPDEConstrainedObj(
Lagrangian, u, u0, lambda, lambda0, alpha, alpha0,
solver));
Vector<double> xInit = obj->getInit();
bool doFDCheck = false;
if (doFDCheck)
{
Out::root() << "Doing FD check of gradient..." << endl;
bool fdOK = obj->fdCheck(xInit, 1.0e-6, 2);
if (fdOK)
{
Out::root() << "FD check OK" << endl;
}
else
{
Out::root() << "FD check FAILED" << endl;
}
}
RCP<UnconstrainedOptimizerBase> opt
= OptBuilder::createOptimizer("basicLMBFGS.xml");
opt->setVerb(2);
OptState state = opt->run(obj, xInit);
bool ok = true;
if (state.status() != Opt_Converged)
{
Out::root()<< "optimization failed: " << state.status() << endl;
TEUCHOS_TEST_FOR_EXCEPT(state.status() != Opt_Converged);
}
Out::root() << "opt converged: " << state.iter() << " iterations"
<< endl;
Out::root() << "exact solution: U0=" << U0 << " A0=" << A0 << endl;
FieldWriter w = new VTKWriter("PoissonSourceInversion");
w.addMesh(mesh);
w.addField("u", new ExprFieldWrapper(u0));
w.addField("alpha", new ExprFieldWrapper(alpha0));
w.addField("lambda", new ExprFieldWrapper(lambda0));
w.write();
double uErr = L2Norm(mesh, interior, u0-U0*uStar, q4);
double aErr = L2Norm(mesh, interior, alpha0-A0*uStar, q4);
Out::root() << "error in u = " << uErr << endl;
Out::root() << "error in alpha = " << aErr << endl;
double tol = 0.01;
Sundance::passFailTest(uErr + aErr, tol);
}
catch(std::exception& e)
{
cerr << "main() caught exception: " << e.what() << endl;
}
Sundance::finalize();
return Sundance::testStatus();
}
int main(int argc, char** argv)
{
try
{
int nx = 32;
double convTol = 1.0e-8;
double lambda = 0.5;
Sundance::setOption("nx", nx, "Number of elements");
Sundance::setOption("tol", convTol, "Convergence tolerance");
Sundance::setOption("lambda", lambda, "Lambda (parameter in Bratu's equation)");
Sundance::init(&argc, &argv);
Out::root() << "Bratu problem (lambda=" << lambda << ")" << endl;
Out::root() << "Newton's method, linearized by hand" << endl << endl;
VectorType<double> vecType = new EpetraVectorType();
MeshType meshType = new BasicSimplicialMeshType();
MeshSource mesher = new PartitionedLineMesher(0.0, 1.0, nx, meshType);
Mesh mesh = mesher.getMesh();
CellFilter interior = new MaximalCellFilter();
CellFilter sides = new DimensionalCellFilter(mesh.spatialDim()-1);
CellFilter left = sides.subset(new CoordinateValueCellPredicate(0, 0.0));
CellFilter right = sides.subset(new CoordinateValueCellPredicate(0, 1.0));
BasisFamily basis = new Lagrange(1);
Expr w = new UnknownFunction(basis, "w");
Expr v = new TestFunction(basis, "v");
Expr grad = gradient(1);
Expr x = new CoordExpr(0);
const double pi = 4.0*atan(1.0);
Expr uExact = sin(pi*x);
Expr R = pi*pi*uExact - lambda*exp(uExact);
QuadratureFamily quad4 = new GaussianQuadrature(4);
QuadratureFamily quad2 = new GaussianQuadrature(2);
DiscreteSpace discSpace(mesh, basis, vecType);
Expr uPrev = new DiscreteFunction(discSpace, 0.5);
Expr stepVal = copyDiscreteFunction(uPrev);
Expr eqn
= Integral(interior, (grad*v)*(grad*w) + (grad*v)*(grad*uPrev)
- v*lambda*exp(uPrev)*(1.0+w) - v*R, quad4);
Expr h = new CellDiameterExpr();
Expr bc = EssentialBC(left+right, v*(uPrev+w)/h, quad2);
LinearProblem prob(mesh, eqn, bc, v, w, vecType);
LinearSolver<double> linSolver
= LinearSolverBuilder::createSolver("amesos.xml");
Out::root() << "Newton iteration" << endl;
int maxIters = 20;
Expr soln ;
bool converged = false;
for (int i=0; i<maxIters; i++)
{
/* solve for the next u */
prob.solve(linSolver, stepVal);
Vector<double> stepVec = getDiscreteFunctionVector(stepVal);
double deltaU = stepVec.norm2();
Out::root() << "Iter=" << setw(3) << i << " ||Delta u||=" << setw(20)
<< deltaU << endl;
addVecToDiscreteFunction(uPrev, stepVec);
if (deltaU < convTol)
{
soln = uPrev;
converged = true;
break;
}
}
TEUCHOS_TEST_FOR_EXCEPTION(!converged, std::runtime_error,
"Newton iteration did not converge after "
<< maxIters << " iterations");
FieldWriter writer = new DSVWriter("HandCodedBratu.dat");
writer.addMesh(mesh);
writer.addField("soln", new ExprFieldWrapper(soln[0]));
writer.write();
Out::root() << "Converged!" << endl << endl;
double L2Err = L2Norm(mesh, interior, soln-uExact, quad4);
Out::root() << "L2 Norm of error: " << L2Err << endl;
Sundance::passFailTest(L2Err, 1.5/((double) nx*nx));
}
catch(std::exception& e)
{
Sundance::handleException(e);
}
Sundance::finalize();
}
int main(int argc, char** argv)
{
try
{
const double pi = 4.0*atan(1.0);
double lambda = 1.25*pi*pi;
int nx = 32;
int nt = 10;
double tFinal = 1.0/lambda;
Sundance::setOption("nx", nx, "Number of elements");
Sundance::setOption("nt", nt, "Number of timesteps");
Sundance::setOption("tFinal", tFinal, "Final time");
Sundance::init(&argc, &argv);
/* Creation of vector type */
VectorType<double> vecType = new EpetraVectorType();
/* Set up mesh */
MeshType meshType = new BasicSimplicialMeshType();
MeshSource meshSrc = new PartitionedRectangleMesher(
0.0, 1.0, nx,
0.0, 1.0, nx,
meshType);
Mesh mesh = meshSrc.getMesh();
/*
* Specification of cell filters
*/
CellFilter interior = new MaximalCellFilter();
CellFilter edges = new DimensionalCellFilter(1);
CellFilter west = edges.coordSubset(0, 0.0);
CellFilter east = edges.coordSubset(0, 1.0);
CellFilter south = edges.coordSubset(1, 0.0);
CellFilter north = edges.coordSubset(1, 1.0);
/* set up test and unknown functions */
BasisFamily basis = new Lagrange(1);
Expr u = new UnknownFunction(basis, "u");
Expr v = new TestFunction(basis, "v");
/* set up differential operators */
Expr grad = gradient(2);
Expr x = new CoordExpr(0);
Expr y = new CoordExpr(1);
Expr t = new Sundance::Parameter(0.0);
Expr tPrev = new Sundance::Parameter(0.0);
DiscreteSpace discSpace(mesh, basis, vecType);
Expr uExact = cos(0.5*pi*y)*sin(pi*x)*exp(-lambda*t);
L2Projector proj(discSpace, uExact);
Expr uPrev = proj.project();
/*
* We need a quadrature rule for doing the integrations
*/
QuadratureFamily quad = new GaussianQuadrature(2);
double deltaT = tFinal/nt;
Expr gWest = -pi*exp(-lambda*t)*cos(0.5*pi*y);
Expr gWestPrev = -pi*exp(-lambda*tPrev)*cos(0.5*pi*y);
/* Create the weak form */
Expr eqn = Integral(interior, v*(u-uPrev)/deltaT
+ 0.5*(grad*v)*(grad*u + grad*uPrev), quad)
+ Integral(west, -0.5*v*(gWest+gWestPrev), quad);
Expr bc = EssentialBC(east + north, v*u, quad);
LinearProblem prob(mesh, eqn, bc, v, u, vecType);
LinearSolver<double> solver
= LinearSolverBuilder::createSolver("amesos.xml");
FieldWriter w0 = new VTKWriter("TransientHeat2D-0");
w0.addMesh(mesh);
w0.addField("T", new ExprFieldWrapper(uPrev[0]));
w0.write();
for (int i=0; i<nt; i++)
{
t.setParameterValue((i+1)*deltaT);
tPrev.setParameterValue(i*deltaT);
Out::root() << "t=" << (i+1)*deltaT << endl;
Expr uNext = prob.solve(solver);
ostringstream oss;
oss << "TransientHeat2D-" << i+1;
FieldWriter w = new VTKWriter(oss.str());
w.addMesh(mesh);
w.addField("T", new ExprFieldWrapper(uNext[0]));
w.write();
updateDiscreteFunction(uNext, uPrev);
}
double err = L2Norm(mesh, interior, uExact-uPrev, quad);
Out::root() << "error norm=" << err << endl;
double h = 1.0/(nx-1.0);
double tol = 0.1*(pow(h,2.0) + pow(lambda*deltaT, 2.0));
Out::root() << "tol=" << tol << endl;
Sundance::passFailTest(err, tol);
}
catch(std::exception& e)
{
Sundance::handleException(e);
}
Sundance::finalize();
return Sundance::testStatus();
}
int main(int argc, char** argv)
{
try
{
Sundance::init(&argc, &argv);
int np = MPIComm::world().getNProc();
int nx = 64;
const double pi = 4.0*atan(1.0);
MeshType meshType = new BasicSimplicialMeshType();
MeshSource mesher = new PartitionedLineMesher(0.0, pi, nx, meshType);
Mesh mesh = mesher.getMesh();
CellFilter interior = new MaximalCellFilter();
CellFilter bdry = new BoundaryCellFilter();
/* Create a vector space factory, used to
* specify the low-level linear algebra representation */
VectorType<double> vecType = new EpetraVectorType();
/* create symbolic coordinate functions */
Expr x = new CoordExpr(0);
/* create target function */
double R = 0.01;
Expr sx = sin(x);
Expr cx = cos(x);
Expr ssx = sin(sx);
Expr sx2 = sx*sx;
Expr cx2 = cx*cx;
Expr f = sx2 - sx - ssx;
Expr uStar = 2.0*R*(sx2-cx2) + R*sx2*ssx + sx;
/* Form exact solution */
Expr uEx = sx;
Expr lambdaEx = R*sx2;
Expr alphaEx = -lambdaEx/R;
/* create a discrete space on the mesh */
BasisFamily bas = new Lagrange(1);
DiscreteSpace discreteSpace(mesh, bas, vecType);
/* initialize the design, state, and multiplier vectors to constants */
Expr alpha0 = new DiscreteFunction(discreteSpace, 0.25, "alpha0");
Expr u0 = new DiscreteFunction(discreteSpace, 0.5, "u0");
Expr lambda0 = new DiscreteFunction(discreteSpace, 0.25, "lambda0");
/* create symbolic objects for test and unknown functions */
Expr u = new UnknownFunction(bas, "u");
Expr lambda = new UnknownFunction(bas, "lambda");
Expr alpha = new UnknownFunction(bas, "alpha");
/* create symbolic differential operators */
Expr dx = new Derivative(0);
Expr grad = dx;
/* create quadrature rules of different orders */
QuadratureFamily q1 = new GaussianQuadrature(1);
QuadratureFamily q2 = new GaussianQuadrature(2);
QuadratureFamily q4 = new GaussianQuadrature(4);
/* Form objective function */
Expr reg = Integral(interior, 0.5 * R * alpha*alpha, q2);
Expr fit = Integral(interior, 0.5 * pow(u-uStar, 2.0), q4);
Expr constraintEqn = Integral(interior,
(grad*lambda)*(grad*u) + lambda*(alpha + sin(u) + f), q4);
Expr L = reg + fit + constraintEqn;
Expr constraintBC = EssentialBC(bdry, lambda*u, q2);
Functional Lagrangian(mesh, L, constraintBC, vecType);
LinearSolver<double> adjSolver
= LinearSolverBuilder::createSolver("amesos.xml");
ParameterXMLFileReader reader("nox-amesos.xml");
ParameterList noxParams = reader.getParameters();
NOXSolver nonlinSolver(noxParams);
RCP<PDEConstrainedObjBase> obj = rcp(new NonlinearPDEConstrainedObj(
Lagrangian, u, u0, lambda, lambda0, alpha, alpha0,
nonlinSolver, adjSolver));
Vector<double> xInit = obj->getInit();
bool doFDCheck = true;
if (doFDCheck)
{
Out::root() << "Doing FD check of gradient..." << endl;
bool fdOK = obj->fdCheck(xInit, 1.0e-6, 0);
if (fdOK)
{
Out::root() << "FD check OK" << endl;
}
else
{
Out::root() << "FD check FAILED" << endl;
TEUCHOS_TEST_FOR_EXCEPT(!fdOK);
}
}
RCP<UnconstrainedOptimizerBase> opt
= OptBuilder::createOptimizer("basicLMBFGS.xml");
opt->setVerb(3);
OptState state = opt->run(obj, xInit);
if (state.status() != Opt_Converged)
{
Out::root()<< "optimization failed: " << state.status() << endl;
TEUCHOS_TEST_FOR_EXCEPT(state.status() != Opt_Converged);
}
else
{
Out::root() << "opt converged: " << state.iter() << " iterations"
<< endl;
}
FieldWriter w = new MatlabWriter("NonlinControl1D");
w.addMesh(mesh);
w.addField("u", new ExprFieldWrapper(u0));
w.addField("alpha", new ExprFieldWrapper(alpha0));
w.addField("lambda", new ExprFieldWrapper(lambda0));
w.write();
double uErr = L2Norm(mesh, interior, u0-uEx, q4);
double lamErr = L2Norm(mesh, interior, lambda0-lambdaEx, q4);
double aErr = L2Norm(mesh, interior, alpha0-alphaEx, q4);
Out::root() << "error in u = " << uErr << endl;
Out::root() << "error in lambda = " << lamErr << endl;
Out::root() << "error in alpha = " << aErr << endl;
double tol = 0.05;
Sundance::passFailTest(uErr + lamErr + aErr, tol);
}
catch(exception& e)
{
cerr << "main() caught exception: " << e.what() << endl;
}
Sundance::finalize();
return Sundance::testStatus();
}
/*
* perform sparse coding with a learned dictionary.
*/
double MedSTC::sparse_coding(Document *doc, const int &docIx,
Params *param, double* theta, double **s )
{
double *sPtr = NULL, *bPtr = NULL, dval = 0;
// initialize mu & theta
double dThetaRatio = m_dGamma / (m_dLambda + doc->length * m_dGamma);
int svmMuIx = docIx * m_nLabelNum;
int gndIx = doc->gndlabel * m_nK;
int nWrd = 0, xVal = 0, k, n;
for ( k=0; k<m_nK; k++ ) {
theta[k] = 0;
}
for ( n=0; n<doc->length; n++ ) {
mu_[n] = 0 + m_dPoisOffset;
nWrd = doc->words[n];
sPtr = s[n];
bPtr = m_dLogProbW[nWrd];
for ( k=0; k<m_nK; k++ ) {
dval = sPtr[k];
if ( dval > 0 ) {
mu_[n] += dval * bPtr[k];
theta[k] += dval;
}
}
}
// initialize theta
for ( k=0; k<m_nK; k++ ) {
theta[k] = theta[k] * dThetaRatio;
}
if ( param->SUPERVISED == 1 ) {
if ( param->PRIMALSVM == 1 ) {
if ( doc->lossAugLabel != -1 && doc->lossAugLabel != doc->gndlabel ) {
int lossIx = doc->lossAugLabel * m_nK;
double dHingeRatio = 0.5 * m_dC / (m_dLambda + doc->length * m_dGamma);
for ( k=0; k<m_nK; k++ ) {
theta[k] += (m_dEta[gndIx+k] - m_dEta[lossIx+k]) * dHingeRatio ;
theta[k] = max(0.0, theta[k]); // enforce theta to be non-negative.
}
}
} else {
double dHingeRatio = 0.5 / (m_dLambda + doc->length * m_dGamma);
for ( k=0; k<m_nK; k++ ) {
for ( int m=0; m<m_nLabelNum; m++ ) {
int yIx = m * m_nK;
theta[k] += m_dMu[svmMuIx+m] * (m_dEta[gndIx+k] - m_dEta[yIx+k]) * dHingeRatio ;
}
theta[k] = max(0.0, theta[k]); // enforce theta to be non-negative.
}
}
} else;
// alternating minimization over theta & s.
double dconverged=1, fval, dobj_val, dpreVal=1;
double mu, eta, beta, aVal, bVal, cVal, discVal, sqrtDiscVal;
double s1, s2;
int it = 0;
while (((dconverged < 0) || (dconverged > param->VAR_CONVERGED)
|| (it <= 2)) && (it <= param->VAR_MAX_ITER))
{
for ( n=0; n<doc->length; n++ ) {
nWrd = doc->words[n];
xVal = doc->counts[n];
bPtr = m_dLogProbW[nWrd];
// optimize over s.
sPtr = s[n];
for ( k=0; k<m_nK; k++ ) {
sold_[k] = sPtr[k];
beta = bPtr[k];
if ( beta > MIN_BETA ) {
mu = mu_[n] - sold_[k] * beta;
eta = beta + m_dRho - 2 * m_dGamma * theta[k];
// solve the quadratic equation.
aVal = 2 * m_dGamma * beta;
bVal = 2 * m_dGamma * mu + beta * eta;
cVal = mu * eta - xVal * beta;
discVal = bVal * bVal - 4 * aVal * cVal;
sqrtDiscVal = sqrt( discVal );
s1 = max(0.0, (sqrtDiscVal - bVal) / (2*aVal)); // non-negative
s2 = max(0.0, 0 - (sqrtDiscVal + bVal) / (2*aVal)); // non-negative
sPtr[k] = max(s1, s2);
} else {
// solve the degenerated linear equation
sPtr[k] = max(0.0, theta[k] - 0.5*m_dRho/m_dGamma);
}
// update mu.
mu_[n] += (sPtr[k] - sold_[k]) * beta;
}
// update theta.
for ( k=0; k<m_nK; k++ ) {
theta[k] += (sPtr[k] - sold_[k]) * dThetaRatio;
theta[k] = max(0.0, theta[k]); // enforce theta to be non-negative.
}
}
// check optimality condition.
fval = 0;
m_dLogLoss = 0;
for ( n=0; n<doc->length; n++ ) {
double dval = mu_[n];
double dLogLoss = (dval - doc->counts[n] * log(dval));
m_dLogLoss += dLogLoss;
fval += dLogLoss + m_dGamma * L2Dist(s[n], theta, m_nK)
+ m_dRho * L1Norm(s[n], m_nK);
}
fval += m_dLambda * L2Norm(theta, m_nK);
dobj_val = fval;
if ( param->SUPERVISED == 1 ) { // compute svm objective
if ( param->PRIMALSVM == 1 ) {
if ( doc->lossAugLabel != -1 && doc->lossAugLabel != doc->gndlabel ) { // hinge loss
int lossIx = doc->lossAugLabel * m_nK;
dval = loss( doc->gndlabel, doc->lossAugLabel );
for ( k=0; k<m_nK; k++ ) {
dval += theta[k] * (m_dEta[lossIx+k] - m_dEta[gndIx+k]);
}
dobj_val += m_dC * dval;
}
} else {
for ( int m=0; m<m_nLabelNum; m++ ) {
int yIx = m * m_nK;
dval = loss( doc->gndlabel, m );
for ( k=0; k<m_nK; k++ ) {
dval += theta[k] * (m_dEta[yIx+k] - m_dEta[gndIx+k]);
}
dobj_val += m_dMu[svmMuIx+m] * dval;
}
}
}
dconverged = (dpreVal - dobj_val) / dpreVal;
dpreVal = dobj_val;
it ++;
}
return fval;
}
int main(int argc, char** argv)
{
try
{
int nx = 32;
double convTol = 1.0e-8;
double lambda = 0.5;
Sundance::setOption("nx", nx, "Number of elements");
Sundance::setOption("tol", convTol, "Convergence tolerance");
Sundance::setOption("lambda", lambda, "Lambda (parameter in Bratu's equation)");
Sundance::init(&argc, &argv);
Out::root() << "Bratu problem (lambda=" << lambda << ")" << endl;
Out::root() << "Fixed-point iteration" << endl << endl;
VectorType<double> vecType = new EpetraVectorType();
MeshType meshType = new BasicSimplicialMeshType();
MeshSource mesher = new PartitionedLineMesher(0.0, 1.0, nx, meshType);
Mesh mesh = mesher.getMesh();
CellFilter interior = new MaximalCellFilter();
CellFilter sides = new DimensionalCellFilter(mesh.spatialDim()-1);
CellFilter left = sides.subset(new CoordinateValueCellPredicate(0, 0.0));
CellFilter right = sides.subset(new CoordinateValueCellPredicate(0, 1.0));
BasisFamily basis = new Lagrange(1);
Expr u = new UnknownFunction(basis, "u");
Expr v = new TestFunction(basis, "v");
Expr grad = gradient(1);
Expr x = new CoordExpr(0);
const double pi = 4.0*atan(1.0);
Expr uExact = sin(pi*x);
Expr R = pi*pi*uExact - lambda*exp(uExact);
QuadratureFamily quad4 = new GaussianQuadrature(4);
QuadratureFamily quad2 = new GaussianQuadrature(2);
DiscreteSpace discSpace(mesh, basis, vecType);
Expr uPrev = new DiscreteFunction(discSpace, 0.5);
Expr uCur = copyDiscreteFunction(uPrev);
Expr eqn
= Integral(interior, (grad*u)*(grad*v) - v*lambda*exp(uPrev) - v*R, quad4);
Expr h = new CellDiameterExpr();
Expr bc = EssentialBC(left+right, v*u/h, quad4);
LinearProblem prob(mesh, eqn, bc, v, u, vecType);
Expr normSqExpr = Integral(interior, pow(u-uPrev, 2.0), quad2);
Functional normSqFunc(mesh, normSqExpr, vecType);
FunctionalEvaluator normSqEval = normSqFunc.evaluator(u, uCur);
LinearSolver<double> linSolver
= LinearSolverBuilder::createSolver("amesos.xml");
Out::root() << "Fixed-point iteration" << endl;
int maxIters = 20;
Expr soln ;
bool converged = false;
for (int i=0; i<maxIters; i++)
{
/* solve for the next u */
prob.solve(linSolver, uCur);
/* evaluate the norm of (uCur-uPrev) using
* the FunctionalEvaluator defined above */
double deltaU = sqrt(normSqEval.evaluate());
Out::root() << "Iter=" << setw(3) << i << " ||Delta u||=" << setw(20)
<< deltaU << endl;
/* check for convergence */
if (deltaU < convTol)
{
soln = uCur;
converged = true;
break;
}
/* get the vector from the current discrete function */
Vector<double> uVec = getDiscreteFunctionVector(uCur);
/* copy the vector into the previous discrete function */
setDiscreteFunctionVector(uPrev, uVec);
}
TEUCHOS_TEST_FOR_EXCEPTION(!converged, std::runtime_error,
"Fixed point iteration did not converge after "
<< maxIters << " iterations");
FieldWriter writer = new DSVWriter("FixedPointBratu.dat");
writer.addMesh(mesh);
writer.addField("soln", new ExprFieldWrapper(soln[0]));
writer.write();
Out::root() << "Converged!" << endl << endl;
double L2Err = L2Norm(mesh, interior, soln-uExact, quad4);
Out::root() << "L2 Norm of error: " << L2Err << endl;
Sundance::passFailTest(L2Err, 1.5/((double) nx*nx));
}
catch(exception& e)
{
Sundance::handleException(e);
}
Sundance::finalize();
}
int main(int argc, char** argv)
{
try
{
int nx = 32;
double convTol = 1.0e-8;
double lambda = 0.5;
Sundance::setOption("nx", nx, "Number of elements");
Sundance::setOption("tol", convTol, "Convergence tolerance");
Sundance::setOption("lambda", lambda, "Lambda (parameter in Bratu's equation)");
Sundance::init(&argc, &argv);
Out::root() << "Bratu problem (lambda=" << lambda << ")" << endl;
Out::root() << "Newton's method with automated linearization"
<< endl << endl;
VectorType<double> vecType = new EpetraVectorType();
MeshType meshType = new BasicSimplicialMeshType();
MeshSource mesher = new PartitionedLineMesher(0.0, 1.0, nx, meshType);
Mesh mesh = mesher.getMesh();
CellFilter interior = new MaximalCellFilter();
CellFilter sides = new DimensionalCellFilter(mesh.spatialDim()-1);
CellFilter left = sides.subset(new CoordinateValueCellPredicate(0, 0.0));
CellFilter right = sides.subset(new CoordinateValueCellPredicate(0, 1.0));
BasisFamily basis = new Lagrange(1);
Expr u = new UnknownFunction(basis, "w");
Expr v = new TestFunction(basis, "v");
Expr grad = gradient(1);
Expr x = new CoordExpr(0);
const double pi = 4.0*atan(1.0);
Expr uExact = sin(pi*x);
Expr R = pi*pi*uExact - lambda*exp(uExact);
QuadratureFamily quad4 = new GaussianQuadrature(4);
QuadratureFamily quad2 = new GaussianQuadrature(2);
DiscreteSpace discSpace(mesh, basis, vecType);
Expr uPrev = new DiscreteFunction(discSpace, 0.5);
Expr eqn
= Integral(interior, (grad*v)*(grad*u) - v*lambda*exp(u) - v*R, quad4);
Expr h = new CellDiameterExpr();
Expr bc = EssentialBC(left+right, v*u/h, quad2);
NonlinearProblem prob(mesh, eqn, bc, v, u, uPrev, vecType);
NonlinearSolver<double> solver
= NonlinearSolverBuilder::createSolver("playa-newton-amesos.xml");
Out::root() << "Newton solve" << endl;
SolverState<double> state = prob.solve(solver);
TEUCHOS_TEST_FOR_EXCEPTION(state.finalState() != SolveConverged,
std::runtime_error,
"Nonlinear solve failed to converge: message=" << state.finalMsg());
Expr soln = uPrev;
FieldWriter writer = new DSVWriter("AutoLinearizedBratu.dat");
writer.addMesh(mesh);
writer.addField("soln", new ExprFieldWrapper(soln[0]));
writer.write();
Out::root() << "Converged!" << endl << endl;
double L2Err = L2Norm(mesh, interior, soln-uExact, quad4);
Out::root() << "L2 Norm of error: " << L2Err << endl;
Sundance::passFailTest(L2Err, 1.5/((double) nx*nx));
}
catch(std::exception& e)
{
Sundance::handleException(e);
}
Sundance::finalize();
return Sundance::testStatus();
}
void FluxTrace<D>::T_CalcElementMatrix (const FiniteElement & base_fel,
const ElementTransformation & eltrans,
FlatMatrix<SCAL> elmat,
LocalHeap & lh) const {
const CompoundFiniteElement & cfel // product space
= dynamic_cast<const CompoundFiniteElement&> (base_fel);
const HDivFiniteElement<D> & fel_q = // q space
dynamic_cast<const HDivFiniteElement<D>& > (cfel[GetInd1()]);
const ScalarFiniteElement<D> & fel_e = // e space
dynamic_cast<const ScalarFiniteElement<D>&> (cfel[GetInd2()]);
elmat = SCAL(0.0);
IntRange rq = cfel.GetRange(GetInd1());
IntRange re = cfel.GetRange(GetInd2());
int ndofq = rq.Size();
int ndofe = re.Size();
FlatMatrix<SCAL> submat(ndofe,ndofq,lh);
FlatMatrixFixWidth<D> shapeq(ndofq,lh); // q-basis (vec) values
FlatVector<> shapee(ndofe,lh); // e-basis basis
ELEMENT_TYPE eltype // get the type of element:
= fel_q.ElementType(); // ET_TRIG in 2d, ET_TET in 3d.
// transform facet integration points to volume integration points
Facet2ElementTrafo transform(eltype);
int nfa = ElementTopology::GetNFacets(eltype); /* nfa = number of facets
of an element */
submat = 0.0;
for(int k = 0; k<nfa; k++) {
// type of geometry of k-th facet
ELEMENT_TYPE eltype_facet = ElementTopology::GetFacetType(eltype, k);
const IntegrationRule & facet_ir =
SelectIntegrationRule (eltype_facet, fel_q.Order()+fel_e.Order());
// reference element normal vector
FlatVec<D> normal_ref = ElementTopology::GetNormals(eltype) [k];
for (int l = 0; l < facet_ir.GetNIP(); l++) {
// map 1D facet points to volume integration points
IntegrationPoint volume_ip = transform(k, facet_ir[l]);
MappedIntegrationPoint<D,D> mip (volume_ip, eltrans);
// compute normal on physcial element
Mat<D> inv_jac = mip.GetJacobianInverse();
double det = mip.GetJacobiDet();
Vec<D> normal = fabs(det) * Trans(inv_jac) * normal_ref;
double len = L2Norm(normal);
normal /= len;
double weight = facet_ir[l].Weight()*len;
// mapped H(div) basis fn values and DG fn (no need to map) values
fel_q.CalcMappedShape(mip,shapeq);
fel_e.CalcShape(volume_ip,shapee);
// evaluate coefficient
SCAL dd = coeff_d -> T_Evaluate<SCAL>(mip);
// [ndofe x 1] [ndofq x D] * [D x 1]
submat += (dd*weight) * shapee * Trans( shapeq * normal ) ;
}
}
elmat.Rows(re).Cols(rq) += submat;
elmat.Rows(rq).Cols(re) += Conj(Trans(submat));
}
void NeumannVolume<D> ::
T_CalcElementVector (const FiniteElement & base_fel,
const ElementTransformation & eltrans,
FlatVector<SCAL> elvec,
LocalHeap & lh) const {
const CompoundFiniteElement & cfel
= dynamic_cast<const CompoundFiniteElement&> (base_fel);
const ScalarFiniteElement<D> & fel =
dynamic_cast<const ScalarFiniteElement<D>&> (cfel[indx]);
FlatVector<> ushape(fel.GetNDof(), lh);
elvec = SCAL(0);
IntRange re = cfel.GetRange(indx);
int ndofe = re.Size();
FlatVector<SCAL> subvec(ndofe,lh);
subvec = SCAL(0);
const IntegrationRule ir(fel.ElementType(), 2*fel.Order());
ELEMENT_TYPE eltype = base_fel.ElementType();
int nfacet = ElementTopology::GetNFacets(eltype);
Facet2ElementTrafo transform(eltype);
FlatVector< Vec<D> > normals = ElementTopology::GetNormals<D>(eltype);
const MeshAccess & ma = *(const MeshAccess*)eltrans.GetMesh();
Array<int> fnums, sels;
ma.GetElFacets (eltrans.GetElementNr(), fnums);
for (int k = 0; k < nfacet; k++) {
ma.GetFacetSurfaceElements (fnums[k], sels);
// if interior element, then do nothing:
if (sels.Size() == 0) continue;
// else:
Vec<D> normal_ref = normals[k];
ELEMENT_TYPE etfacet = ElementTopology::GetFacetType (eltype, k);
IntegrationRule ir_facet(etfacet, 2*fel.Order());
// map the facet integration points to volume reference elt ipts
IntegrationRule & ir_facet_vol = transform(k, ir_facet, lh);
// ... and further to the physical element
MappedIntegrationRule<D,D> mir(ir_facet_vol, eltrans, lh);
for (int i = 0 ; i < ir_facet_vol.GetNIP(); i++) {
SCAL G[3] ;
G[0] = coeff_Gx -> T_Evaluate<SCAL>(mir[i]);
G[1] = coeff_Gy -> T_Evaluate<SCAL>(mir[i]);
if (D==3) G[2] = coeff_Gz -> T_Evaluate<SCAL>(mir[i]);
FlatVector<SCAL> Gval(D,lh);
for (int dd=0; dd<D; dd++) Gval[dd] = G[dd];
SCAL g = coeff_g -> T_Evaluate<SCAL>(mir[i]);
// this is contrived to get the surface measure in "len"
Mat<D> inv_jac = mir[i].GetJacobianInverse();
double det = mir[i].GetMeasure();
Vec<D> normal = det * Trans (inv_jac) * normal_ref;
double len = L2Norm (normal);
SCAL gg = (InnerProduct(Gval,normal) + g*len)
* ir_facet[i].Weight();
fel.CalcShape (ir_facet_vol[i], ushape);
subvec += gg * ushape;
}
}
elvec.Rows(re) += subvec;
}
void RobinVolume<D> ::
T_CalcElementMatrix (const FiniteElement & base_fel,
const ElementTransformation & eltrans,
FlatMatrix<SCAL> elmat,
LocalHeap & lh) const {
ELEMENT_TYPE eltype
= base_fel.ElementType();
const CompoundFiniteElement & cfel // product space
= dynamic_cast<const CompoundFiniteElement&> (base_fel);
// note how we do NOT refer to D-1 elements here:
const ScalarFiniteElement<D> & fel_u = // u space
dynamic_cast<const ScalarFiniteElement<D>&> (cfel[GetInd1()]);
const ScalarFiniteElement<D> & fel_e = // e space
dynamic_cast<const ScalarFiniteElement<D>&> (cfel[GetInd2()]);
elmat = SCAL(0);
IntRange ru = cfel.GetRange(GetInd1());
IntRange re = cfel.GetRange(GetInd2());
int ndofe = re.Size();
int ndofu = ru.Size();
FlatVector<> ushape(fel_u.GetNDof(), lh);
FlatVector<> eshape(fel_e.GetNDof(), lh);
FlatMatrix<SCAL> submat(ndofe,ndofu,lh);
submat = SCAL(0);
int nfacet = ElementTopology::GetNFacets(eltype);
Facet2ElementTrafo transform(eltype);
FlatVector< Vec<D> > normals = ElementTopology::GetNormals<D>(eltype);
const MeshAccess & ma = *(const MeshAccess*)eltrans.GetMesh();
Array<int> fnums, sels;
ma.GetElFacets (eltrans.GetElementNr(), fnums);
for (int k = 0; k < nfacet; k++) {
ma.GetFacetSurfaceElements (fnums[k], sels);
// if interior element, then do nothing:
if (sels.Size() == 0) continue;
// else:
Vec<D> normal_ref = normals[k];
ELEMENT_TYPE etfacet=ElementTopology::GetFacetType(eltype, k);
IntegrationRule ir_facet(etfacet, fel_e.Order()+fel_u.Order());
// map the facet integration points to volume reference elt ipts
IntegrationRule & ir_facet_vol = transform(k, ir_facet, lh);
// ... and further to the physical element
MappedIntegrationRule<D,D> mir(ir_facet_vol, eltrans, lh);
for (int i = 0 ; i < ir_facet_vol.GetNIP(); i++) {
SCAL val = coeff_c->T_Evaluate<SCAL> (mir[i]);
// this is contrived to get the surface measure in "len"
Mat<D> inv_jac = mir[i].GetJacobianInverse();
double det = mir[i].GetMeasure();
Vec<D> normal = det * Trans (inv_jac) * normal_ref;
double len = L2Norm (normal);
val *= len * ir_facet[i].Weight();
fel_u.CalcShape (ir_facet_vol[i], ushape);
fel_e.CalcShape (ir_facet_vol[i], eshape);
submat += val * eshape * Trans(ushape);
}
}
elmat.Rows(re).Cols(ru) += submat;
if (GetInd1() != GetInd2())
elmat.Rows(ru).Cols(re) += Conj(Trans(submat));
}
void TraceTrace<D>::T_CalcElementMatrix (const FiniteElement & base_fel,
const ElementTransformation & eltrans,
FlatMatrix<SCAL> elmat,
LocalHeap & lh) const {
const CompoundFiniteElement & cfel // product space
= dynamic_cast<const CompoundFiniteElement&> (base_fel);
const ScalarFiniteElement<D> & fel_u = // u space
dynamic_cast<const ScalarFiniteElement<D>&> (cfel[GetInd1()]);
const ScalarFiniteElement<D> & fel_e = // e space
dynamic_cast<const ScalarFiniteElement<D>&> (cfel[GetInd2()]);
elmat = SCAL(0.0);
IntRange ru = cfel.GetRange(GetInd1());
IntRange re = cfel.GetRange(GetInd2());
int ndofe = re.Size();
int ndofu = ru.Size();
FlatVector<> shapee(ndofe,lh);
FlatVector<> shapeu(ndofu,lh);
FlatMatrix<SCAL> submat(ndofe,ndofu, lh);
submat = SCAL(0.0);
ELEMENT_TYPE eltype = fel_u.ElementType();
Facet2ElementTrafo transform(eltype);
int nfa = ElementTopology :: GetNFacets(eltype);
for(int k = 0; k<nfa; k++) {
// type of geometry of k-th facet
ELEMENT_TYPE eltype_facet = ElementTopology::GetFacetType(eltype, k);
const IntegrationRule & facet_ir =
SelectIntegrationRule (eltype_facet, fel_u.Order()+fel_e.Order());
// reference element normal vector
FlatVec<D> normal_ref = ElementTopology::GetNormals(eltype) [k];
for (int l = 0; l < facet_ir.GetNIP(); l++) {
// map 1D facet points to volume integration points
IntegrationPoint volume_ip = transform(k, facet_ir[l]);
MappedIntegrationPoint<D,D> mip (volume_ip, eltrans);
// compute normal on physcial element
Mat<D> inv_jac = mip.GetJacobianInverse();
double det = mip.GetJacobiDet();
Vec<D> normal = fabs(det) * Trans(inv_jac) * normal_ref;
double len = L2Norm(normal);
normal /= len;
double weight = facet_ir[l].Weight()*len;
fel_e.CalcShape(volume_ip,shapee);
fel_u.CalcShape(volume_ip,shapeu);
SCAL cc = coeff_c -> T_Evaluate<SCAL>(mip);
// [ndofe x 1] [1 x ndofu]
submat += (cc*weight) * shapee * Trans(shapeu);
}
}
elmat.Rows(re).Cols(ru) += submat;
if (GetInd1() != GetInd2())
elmat.Rows(ru).Cols(re) += Conj(Trans(submat));
}